Compare 38 Looker implementation partners delivering LookML semantic modelling, Looker Studio Pro rollouts, embedded analytics into SaaS products, BigQuery-integrated data marts, and Looker plus Gemini Code Assist programmes since Google's deeper consolidation of the platform under Google Cloud. Listings cover Google Cloud Premier partners with dedicated Looker practices, analytics-engineering boutiques fluent in dbt-to-LookML workflows, and large SIs running multi-year managed Looker estates. Looker remains the strongest enterprise option for governed semantic modelling, but pricing under the consolidated Google Cloud SKU and LookML migration cost from legacy reports continue to shape every business case. Use this directory to shortlist Looker partners by tier, embed scope, and region. No partner pays for placement on this directory.
Looker engagements typically split into four workstreams. LookML semantic modelling, where the partner translates dimensional models or dbt models into LookML views, explores, and dashboards, embedding row-level access controls and aggregate-awareness logic. BigQuery integration, where storage tiering, partitioning, clustering, and BI Engine reservations are tuned to keep Looker queries inside Google's free quota for aggregate-aware paths. Embedded analytics, where Looker is iframed or SDK-integrated into customer-facing SaaS products with SSO, attribute-based filtering, and Looker Powered By branding. Migration from legacy BI (Tableau, MicroStrategy, Cognos, OBIEE) to Looker, typically the most labour-intensive workstream because dashboards must be rebuilt rather than ported.
Three procurement archetypes recur. Premier global SIs (Accenture, Deloitte, Capgemini, Infosys, TCS, Wipro) lead where Looker sits inside a wider Google Cloud or analytics modernisation programme, often co-sold with Google on multi-year mandates. Analytics-engineering boutiques (Datatonic, Rittman, DataDriven, Switchboard) lead on LookML quality, dbt-to-LookML conversion, and embedded analytics where craftsmanship in the semantic layer matters more than scale. Slalom and mid-market specialists lead North American mid-market analytics modernisation. Friction point: Looker pricing under the consolidated Google Cloud SKU rewards heavy BigQuery use but penalises buyers who keep analytics on Snowflake or Redshift; cross-cloud Looker deployments routinely cost 30-60% more per user than BigQuery-native deployments at equivalent scale.
For complementary research see BI platforms, embedded analytics, semantic layers, cloud data warehouses, and data transformation tools. For adjacent services see Tableau implementation, Power BI implementation, dbt implementation, Google Cloud consulting, data engineering, and data lakehouse engineering.
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